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Models for the External Support Component of Moody's Bank Ratings

Author

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  • Peresetsky, Anatoly

    (Higher School of Economics, CEMI RAS and NES, Moscow, Russia)

Abstract

The paper presents an econometric study of the two bank ratings assigned by Moody's Investors Service. We find the models based solely on public information can approximate the ratings reasonably well. It is demonstrated that Moody’s has a special approach for banks in developing countries and in Russia particularly. Models for the (unobserved) external support are presented. The models help reveal factors that are important for the external bank support

Suggested Citation

  • Peresetsky, Anatoly, 2009. "Models for the External Support Component of Moody's Bank Ratings," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 14(2), pages 3-23.
    • Handle: RePEc:ris:apltrx:0029
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    References listed on IDEAS

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    1. Marshall E. Blume & Felix Lim & A. Craig Mackinlay, 1998. "The Declining Credit Quality of U.S. Corporate Debt: Myth or Reality?," Journal of Finance, American Finance Association, vol. 53(4), pages 1389-1413, August.
    2. Amato, Jeffery D. & Furfine, Craig H., 2004. "Are credit ratings procyclical?," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2641-2677, November.
    3. Altman, Edward I. & Saunders, Anthony, 1997. "Credit risk measurement: Developments over the last 20 years," Journal of Banking & Finance, Elsevier, vol. 21(11-12), pages 1721-1742, December.
    4. Marshall E. Blume & Felix Lim & A. Craig MacKinlay, "undated". "The Declining Credit Quality of US Corporate Debt: Myth or Reality?," Rodney L. White Center for Financial Research Working Papers 03-98, Wharton School Rodney L. White Center for Financial Research.
    5. repec:fth:pennfi:67 is not listed on IDEAS
    6. Marshall E. Blume & Felix Lim & A. Craig MacKinlay, "undated". "The Declining Credit Quality of US Corporate Debt: Myth or Reality?," Rodney L. White Center for Financial Research Working Papers 3-98, Wharton School Rodney L. White Center for Financial Research.
    7. Karminsky, Alexandr & Peresetsky, Anatoly, 2007. "Models of Banks Ratings," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 5(1), pages 3-19.
    8. Somerville, R. A. & Taffler, R. J., 1995. "Banker judgement versus formal forecasting models: The case of country risk assessment," Journal of Banking & Finance, Elsevier, vol. 19(2), pages 281-297, May.
    9. Altman, Edward I. & Rijken, Herbert A., 2004. "How rating agencies achieve rating stability," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2679-2714, November.
    10. Kaplan, Robert S & Urwitz, Gabriel, 1979. "Statistical Models of Bond Ratings: A Methodological Inquiry," The Journal of Business, University of Chicago Press, vol. 52(2), pages 231-261, April.
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    Citations

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    Cited by:

    1. Aivazian, Sergey & Golovan, Sergey & Karminsky, Alexander & Peresetsky, Anatoly, 2011. "An approach to ratings mapping," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 23(3), pages 13-40.
    2. Zhivaikina, A. & Peresetsky, A., 2017. "Russian Bank Credit Ratings and Bank License Withdrawal 2012-2016," Journal of the New Economic Association, New Economic Association, vol. 36(4), pages 49-80.
    3. Peresetsky, A. A., 2011. "What factors drive the Russian banks license withdrawal," MPRA Paper 41507, University Library of Munich, Germany.
    4. Ошерович Инна Львовна, 2015. "Анализ вероятностных соответствий меж ду рейтингами ведущих меж дународных компаний Moody’s, Fitch и standard&poor’s," Вестник Финансового университета, CyberLeninka;Федеральное государственное образовательное бюджетное учреждение высшего профессионального образования «Финансовый университет при Правительстве Российской Федерации» (Финансовый университет), issue 3 (87), pages 136-148.
    5. Denis Shibitov & Mariam Mamedli, 2019. "The finer points of model comparison in machine learning: forecasting based on russian banks’ data," Bank of Russia Working Paper Series wps43, Bank of Russia.

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    More about this item

    Keywords

    Bank ratings; rating agency; rating’s model; modeling unobserved factor; matching ratings;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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